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Record W4414162291 · doi:10.1177/10497323251371520

An Exploration of How Parents Did Waiting for Their Child’s Transplant: Inpatient, Outpatient, and Home Space-Times

2025· article· en· W4414162291 on OpenAlexafffund
Kristina Smith, Kelly P. Arbour‐Nicitopoulos, Kimberley Widger

Bibliographic record

VenueQualitative Health Research · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicFamily Support in Illness
Canadian institutionsUniversity of TorontoUniversity of Victoria
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsNarrativeEthnographyWaiting listBone marrow transplantWaiting periodQualitative researchBone marrow transplantation

Abstract

fetched live from OpenAlex

Current evidence shows that waiting for a child’s solid organ, stem cell, or bone marrow transplant can cause social, emotional, and psychological suffering for children and their families. Despite waiting being a central theme, little research has investigated what families do while they are waiting in hospital and home settings and what daily life looks like in these contexts. This narrative ethnographic study explored what waiting may look like for parents of children waiting to receive a solid organ, stem cell, or bone marrow transplant drawing on the notion of space-time. Six parents from four different families participated in interviews and observations that explored the questions: How do parents wait on a daily basis and what does waiting look like in the hospital and home? Our narrative analysis suggested that the structure, rhythms, and flow were complex and diverse in the hospital and home space-time. Inpatient space-time could afford parents comfort by having expectations managed, while unpredictability of outpatient space-time caused immense stress. Waiting at home was a paradox in that it could be busy, monotonous, and isolating. Findings contribute to conceptual and practical work exploring how parents do waiting for their child’s transplant on a daily basis and how they can be supported when they enter into unfamiliar illness narratives.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.140
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.376
GPT teacher head0.545
Teacher spread0.169 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes2
Has abstractyes

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